July 29, 2024

The 1x1 of maintenance measures for machine efficiency

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In the world of machines, “downtime” is the last thing you want as a plant operator. Maintenance measures are considered to be the oil in the transmission that ensures smooth operation and extends the life of your systems. But which specific measures actually fall under the term “maintenance” and how do obvious terms such as maintenance and inspection differ? Our technical article provides an overview and important tips for machine optimization!

Definition: maintenance measures

Maintenance measures are all targeted activities that ensure that machines and systems function properly. They include regular maintenance, repairs and adjustments to avoid unexpected failures and expensive downtimes. Targeted maintenance measures keep production machines efficient and reliable, which ultimately increases productivity and saves costs.

Benefits of maintenance measures

Effective maintenance offers numerous benefits:

1. Increased availability and productivity: Regular maintenance reduces unplanned outages.
2. Cost control: Predictive measures reduce maintenance costs in the long term.
3. Security improvement: Continuous controls minimize security risks.
4. Sustainability: A well-maintained machine has a longer lifespan and reduces resource consumption.

4 types of maintenance measures

Diagram of maintenance measures
1st inspection: Regular inspection of the machine's health status, e.g. visual checks and functional tests, in order to identify wear or damage at an early stage. One example is testing manufacturing robots for mechanical wear and malfunctions.

2. Maintenance: Planned measures to maintain health, such as cleaning, lubrication and replacement of wear parts. One example is the regular replacement of hydraulic filters in production machines to maintain their efficiency.

3. Repair: Repairs to restore health/functionality following a defect. For example, replacing a faulty transmission in a production machine.

4. Improvement: Measures to increase efficiency or safety, such as retrofitting machines with modern sensors for better monitoring. For example, installing vibration sensors to become aware of storage problems at an early stage.

Best practices for effectively carrying out maintenance measures

Strategic planning: A clear maintenance strategy is critical for taking the right action at the right time. Be sure to consider the specific requirements of your machines and production processes.

Using maintenance software: Tools such as the AI-based software from aiomatic assist with data collection and analysis of sensor data as well as the early detection of faults. By the way: Our solution also offers a visual root cause analysis so targeted maintenance work can be carried out.

Regular staff training: Training ensures that personnel are familiar with the latest technologies and processes, which increases maintenance effectiveness.

Use of Predictive Maintenance techniques: Predictive Maintenance solutions use machine learning and data analytics to make predictions about potential failures, which enables proactive measures and maximizes machine availability.

Documentation and logging: Careful documentation of all measures carried out is the key to success. It not only supports traceability, but also the optimization of future maintenance strategies.

Obstacles that make effective maintenance measures difficult

1. Poor data quality and availability: When data on the condition of machines and systems are inaccurate or incomplete, it is difficult to carry out necessary maintenance work in a timely and effective manner.

2. Lack of know-how: A lack of technical knowledge and experience can result in maintenance measures not being carried out optimally, leading to inefficient processes and higher failure rates.

3. Resistance of new technologies: There is often a reluctance to introduce new technologies that would be necessary for more effective maintenance. This resistance may be due to fear of change or a lack of trust in new systems.

4. Technological complexity: The increasing complexity of modern machinery and equipment presents additional challenges as more specialized knowledge and technologies are required to maintain and repair them.

In addition to these points, budget restrictions may also play a role, as there is not always sufficient financial resources available to implement and carry out necessary maintenance measures. Lack of planning and coordination within the company can also lead to inefficient maintenance processes.
Budget restrictions play a role, as there is not always sufficient financial resources available to implement and carry out necessary maintenance measures.

Planning maintenance measures with aiomatic software

Screenshot of the dashboard from aiomatic's software
With aiomatic's software, the planning of maintenance measures is being revolutionized! Artificial intelligence is used to precisely predict maintenance requirements and thus significantly increase efficiency. Instead of relying on rigid maintenance plans or reactive repairs, aiomatic enables data-driven, Predictive Maintenance that minimizes unnecessary costs and wasted resources. See benefits for yourself and book a free demo to find out how aiomatic can also optimize your maintenance strategy.

FAQ

Predictive Maintenance uses sensor data such as temperature, vibration, and pressure to monitor the condition of machines in real time and detect anomalies at an early stage.
Regular Maintenance measures prevent unexpected failures, reduce repair costs and extend the life of the systems.
Maintenance measures should ideally be carried out proactively, based on the actual condition of the machines and systems. Instead of periodic preventive maintenance, which often consumes resources unnecessarily, or reactive maintenance, which can lead to high costs and downtime, the goal should be data-driven and condition-based maintenance. By using sensors and data analyses, the status of the machines can be continuously monitored.

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